Apple's iOS 11 promises to be a big upgrade for shutterbugs. It's improving both the Camera and Photos apps to take some of the headaches out of snapshots and photos. For instance, the Photos app's Memories section can make use of machine learning to automatically reorient images when you change your phone's orientation -- it knows what to focus on. Live Photos also make use of this AI-like technology for effects. And Live Photos should be decidedly liverly with new visual tricks, including a long exposure blur effect, the ability to pick a key photo, video looping and a Boomerang-style "bounce" effect. Also, Apple is making some improvements that will help you capture more photos and videos.

Software is still king at Apple's developers conference, so expect the company to devote lots of time to iOS, macOS and watchOS. The iPad, frankly, has been sucking wind. CEO Tim Cook believe the tablet will eventually replace laptops -- but tell that to buyers. So is it time for an upgrade? RBC Capital expects Apple to announce an improved iPad Pro with faster processors and other enhancements.

The voice recognition could run on the device, but the actual resolution of the question needs a model far too big for a device, which also updates constantly. In the end is easier to send everything to the servers and also use the data for future training.

Deep generative models have achieved impressive success in recent years. Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), as powerful frameworks for deep generative model learning, have largely been considered as two distinct paradigms and received extensive independent study respectively. This paper establishes formal connections between deep generative modeling approaches through a new formulation of GANs and VAEs. We show that GANs and VAEs are essentially minimizing KL divergences with opposite directions and reversed latent/visible treatments, extending the two learning phases of classic wake-sleep algorithm, respectively. The unified view provides a powerful tool to analyze a diverse set of existing model variants, and enables to exchange ideas across research lines in a principled way.

How does DeepMind choose research topics to focus on? Going through DeepMind's publication lists, their focus seems a bit more narrow than other labs. Yet they are probably one of the largest (if not the largest) research group with about 400 people (https://en.wikipedia.org/wiki/DeepMind) . For example, the have a great deal of work on generative models but no work on GANs. They also have a great deal of focus on Reinforcement Learning but not robotics.

Apple is expected to reveal new products and give the public a glimpse of the iOS 11 update during the Worldwide Developers Conference. WWDC will take place from June 5-9 in San Jose, Calif., with the keynote address at 1 P.M. EST Monday. You can watch the event live stream using this link on your MacBook, iPad, iPhone or a PC with Microsoft Edge on Windows 10. You can also watch the keynote address on the Apple TV (second and third generation). Here's what could be announced at WWDC: Apple could give a preview of some features that will be on iOS 11, the upcoming update for iPads and iPhones which is expected to be released this fall alongside the iPhone 8, iPhone 7S and iPhone 7S Plus.

Google is using machine learning to teach computers to sketch and make music, but one engineer says it isn't ready to "generate" a new Beatles album just yet. IN the future, cars will drive themselves, fridges will order groceries, and doors will unlock automatically as you approach. But what happens when computers move beyond chores and take on creative endeavours? What happens when computers start making art? It's a question Google is investigating, not only investing money in making computers code the most efficient programs themselves, but asking them to learn how to draw, and make their own music based on our own.

This is a two-part series about using machine learning to hack my taste in music. In this first piece, I applied unsupervised learning techniques and tools on Pandora data to analyze songs that I like. The second part, which will be published soon, is about using supervised on Spotify data to predict whether or not I will like a song. If you take a look at my top tracks on Last.FM, you'll notice a smorgasbord of tracks from artists like LCD Soundsytem, Jimi Hendrix, and Kanye West. When I make a playlist, it's not uncommon for me to include some 80's post-disco, 2000s indie rock, and Nigerian or Turkish funk.

While AI and machine learning are buzzwords, Symantec's Nick Savvides said, during this year's AusCERT conference they have been a big deal in computing circles since the 1950s. But it was in the 1980s when AI came into mainstream thinking a culture. It was movies like War Games and The Terminator, and TV shows like Knight Rider that took this important technology and moved it into mainstream consciousness. Savvides pointed to KITT, the automotive star of Knight Rider, as an example of what AI might one day deliver. "It had the ability to perceive, to provide constant analysis and make decisions," said Savvides.

This piece was originally published at Scout.ai. "This is a propaganda machine. It's targeting people individually to recruit them to an idea. It's a level of social engineering that I've never seen before. They're capturing people and then keeping them on an emotional leash and never letting them go," said professor Jonathan Albright. Albright, an assistant professor and data scientist at Elon University, started digging into fake news sites after Donald Trump was elected president. Through extensive research and interviews with Albright and other key experts in the field, including Samuel Woolley, Head of Research at Oxford University's Computational Propaganda Project, and Martin Moore, Director of the Centre for the Study of Media, Communication and Power at Kings College, it became clear to Scout that this phenomenon was about much more than just a few fake news stories. It was a piece of a much bigger and darker puzzle -- a Weaponized AI Propaganda Machine being used to manipulate our opinions and behavior to advance specific political agendas. By leveraging automated emotional manipulation alongside swarms of bots, Facebook dark posts, A/B testing, and fake news networks, a company called Cambridge Analytica has activated an invisible machine that preys on the personalities of individual voters to create large shifts in public opinion.